Thejus T. Jayakrishnan, MBBS; Ryan T. Groeschl, MD; Ben George, MD;

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Management of Acute Cholecystitis in Cancer Patients –a Comparative Effectiveness Approach Thejus T. Jayakrishnan, MBBS; Ryan T. Groeschl, MD; Ben George, MD; James P. Thomas, MD, PhD; Sam Pappas, MD; T. Clark Gamblin, MD, MS; Kiran K. Turaga, MD, MPH Department of Surgery

Disclosures I have no relevant financial relationship with the manufacturer(s) of any commercial product(s) and/or provider(s) of commercial service(s) discussed in this CME activity. I do not intend to discuss an unapproved/investigative use of a commercial product/device in my presentation.

Cholecystitis in General Population Commonest etiology – Gallstones 10-15% Gallstone prevalence in the US 1-4% Symptomatic/year1 1Sanders, 2007

Rx Options Surgically fit Cholecystectomy Cholecystostomy/ Surgically unfit Cholecystostomy/ Conservative medical treatment Coagulopathy Neutropenic -Definitive -Recurrence 10-40%

Cholecystitis in Cancer 2. Endoscopy: Biliary stenting 3. Int. Radiology: TACE 1. Surgery: Gastrectomy 4. Drugs: Somatostatins Immunosuppression Cancer Cachexia Increased risk in cancer patients (Relative Risk 1.38)1 1Thomsen, 2008

Management Challenges Increased risk of complications Neutropenia-immunosuppression Advanced age & malnutrition Cholecystectomy vs. no Cholecystectomy Interruption of cancer therapy The risks of recurrence in a limited life span Impact on overall prognosis of the patients Surgical complications - adhesions, thrombocytopenia Metastases

Hypothesis A prognostic model for the management of acute cholecystitis in cancer patients can be developed incorporating patient specific risk factors to yield the optimal survival

Methods Step 1: Generate the base-case scenario – literature review(PubMed) Step 2: Formulate new algorithm Step 3: Decision analyses of new algorithm vs. conventional strategies

Comprehensive search to obtain base-case estimates Methods Comprehensive search to obtain base-case estimates Preliminary search: Literature related to cholecystitis in cancer patients Second search: Risk factors for cholecystitis in cancer patients Therapy related, Cancer related and Host factors Third search: Current management strategies for cholecystitis in the general population

New Algorithm: Initial Management Low Risk Cholecystectomy Re-evaluate surgical risk Start NPO, Analgesics, Antibiotics Low Risk Cholecystectomy Reassess for surgical risk PC High Risk Continue with cholecystostomy Decision analyses High Risk 8 Hours 24 Hours 48 hours 72 hours PC – Percutaneous Cholecystostomy

Decision Tree: Strategies Cx - Cholecystectomy PC – Percutaneous Cholecystostomy TreeAge PRO 2012

Decision Tree: New Algorithm Cx - Cholecystectomy PC – Percutaneous Cholecystostomy

Decision Tree: Follow-up

Probabilities Variable Probability Ranges High risk for surgery   Morbidity Cholecystectomy 0.50 0.10 to 0.60 Percutaneous cholecystostomy 0.10 0.05 to 0.30 Medical management 0.3 0.10 to 0.40 Mortality 0.15 0.05 to 0.50 0.03 0.01 to 0.10 0.05 Low risk for surgery 0.04 0.01 0.005 to 0.05 0.02 0.005 0.001 to 0.01 Percutaneous cholecystostomy 0.001 0.0005 to 0.005 0.002

Assumptions Variable Probability Ranges Reduction in survival due to recurrent cholecystitis 0.05 0.02 to 0.20 Reduction in survival due to interruption to cancer therapy 0.1 0.05 to 0.50

Reference Case 60 year-old patient with advanced cancer with an expected survival of 12 months presenting with acute cholecystitis

Risk Factors for Recurrent Cholecystitis Category Risk Factors Level of evidence 1 Therapy Related Factors   Surgery Gastrectomy Level I Endoscopic procedures ERCP, Stenting Chemotherapy Somatostatin Myelosuppressive drugs Tyrosine Kinase inhibitors: Sunitinib, Sorafenib Level II Level IV Cancer Related Factors General Health Prolonged fasting Total Parenteral Nutrition Weight loss Low Immunity Metastasis Melanoma Renal Cell Carcinoma Host Factors Gallstones Shared risks with cancer Obesity Smoking Estrogen Therapy 1CEBM Levels of Evidence

Results: Estimated Survival For an estimated survival of 12 months: Low surgical risk patients New Algorithm 11.9 months vs. CT 11.8months vs. PC 11.8months vs. DC 11.9months High surgical risk patients New Algorithm 11.6 months vs. DC 9.9 months vs. PC 11.4 months and CT 11 months PC – Percutaneous cholecystostomy Cx - Cholecystectomy

Two-Way Sensitivity Analyses of Probability of Recurrence and Expected Survival Low Moderate High

Discussion PC associated with resolution of acute symptoms 60- 100 % successful clinical resolution 90% resolution in 48-72 hours Length of stay: PC alone > Early cholecystectomy Early cholecystectomy decrease overall hospital length of stay and hospital cost

Limitations The absence of high quality base-case data Hospice or palliative care not incorporated Assumption of constant rates (eg: recurrence) Quality of life and cost-effectiveness not studied

Conclusions A prognostic model based on the premise of “early aggression” and “delayed thoughtfulness” in the management of cholecystitis in patients with advanced malignancies is feasible

Acknowledgement Dr Kiran K. Turaga (Mentor), Dr T. Clark Gamblin Faculty at the Department of Surgery - MCW

THANK YOU